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Quantification of Methane Emissions from Discrete Sources

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2024-05-08

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Chulakadabba, Apisada. 2024. Quantification of Methane Emissions from Discrete Sources. Doctoral dissertation, Harvard University Graduate School of Arts and Sciences.

Abstract

Various point source methane quantification approaches enable comprehensive estimation of methane emissions, which is essential for effective methane monitoring and mitigating strategies. This study uses remote sensing data from projects like MethaneAIR and MethaneSAT to develop robust quantification methods for methane emissions. We explore techniques such as modified integrated mass enhancement (mIME), divergence integral (DI), ratio method, and Geostatistical Inverse Model (GIM) approach, considering factors like the nature of the sources, their size, the background noise, and topography. In the first chapter, we aim to develop rigorous point source quantification approaches for MethaneAIR and MethaneSAT satellites. We explore different techniques to quantify methane emissions from discrete sources and devise a method based on large eddy simulations. Although initially tested on high-resolution Chinese satellites due to the early stage of the MethaneAIR and MethaneSAT projects, these algorithms pave the way for faster development of methods tailored to our projects. In the second chapter, we apply our quantification methods to controlled release experiments and evaluate their performance on MethaneAIR data. Our findings show good agreement between estimated and released emissions as well as mIME and DI quantification methods. We develop a decision tree to determine the most suitable method for specific scenarios, enhancing our understanding of method limitations and informing the development of MethaneSAT algorithms. The final chapter focuses on a detection limit analysis of MethaneAIR to evaluate MethaneSAT’s potential performance. Using large eddy simulations, we estimate MethaneSAT’s detection limit as a function of noise across different resolutions. Additionally, we demonstrated successful point source estimation based on the GIM, bridging the gap between point source and area source quantification techniques. The findings better prepare us for MethaneSAT data analysis. In conclusion, this study lays the foundation for methane point source quantification for the MethaneAIR and MethaneSAT projects. The lessons learned extend beyond our projects; they can allow the appropriate selection of methane emission quantification approaches for various scenarios.

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greenhouse gas, large eddy simulation, methane, remote sensing, Environmental engineering, Environmental science

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